Publications

1977
Article

On the Joint Distribution of Left- and Right-sided Outliner Statistics

By: André Perold and D. M. Hawkins

Keywords: Mathematical Methods

2025
Article

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

By: Kosuke Imai and Michael Lingzhi Li

Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details

Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science

Read Now

Teaching Interest

Overview

I served as a Teaching Fellow for the Applied Business Analytics second-year MBA course. This course sought to teach MBA students how businesses can improve their strategic decisions using statistics and machine learning techniques. (e.g., regression models, random... View Details

Keywords: Analytics; Machine Learning; Statistics

February 2021
Tutorial

Assessing Prediction Accuracy of Machine Learning Models

By: Michael Toffel and Natalie Epstein

This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and... View Details

Keywords: Statistics; Experiments; Forecasting and Prediction; Performance Evaluation; AI and Machine Learning

August 2015 (Revised January 2017)
Technical Note

From Correlation to Causation

By: Feng Zhu and Karim R. Lakhani

To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details

Keywords: Statistics; Regression; Data Analytics; Decisions; Forecasting and Prediction; Judgments

Educators

Teaching Interest

Overview

Graduate student instructor, Introduction to Statistics, 2002
Reader, Introduction to Time Series, 2003
Reader, Introductory Probability Theory, 2001 View Details

Keywords: Statistics; Probability

2015
Chapter

Communicating Statistics in the Context of Banking Union – A Macro User's Perspective

By: Jan Kozak and Huw Pill

Read Now

Article

On Market Timing and Investment Performance Part II: Statistical Procedures for Evaluating Forecasting Skills

By: Robert C. Merton and Roy D. Henriksson

Keywords: Investment; Performance; Mathematical Methods; Forecasting and Prediction

March 2011 (Revised April 2021)
Case

The Whiz Kids

By: Tom Nicholas and David Chen

In October 1945, Henry Ford II received a telegram in his office at the Ford Motor Company in Dearborn, Michigan written by Charles "Tex" Thornton, a U.S. Air Force colonel. The telegram presented an opportunity for Ford to deploy a system of statistical control which... View Details

Keywords: Ford Motor Company; Statistical Control; Management Systems; Accounting; Operations; Strategy; Mathematical Methods; Auto Industry; United States

Educators

September 2009
Article

A Detailed Analysis of the Reduction Mammaplasty Learning Curve: A Statistical Process Model for Approaching Surgical Performance Improvement

By: Matthew Carty MD, Rodney Chan, Robert S. Huckman, Daniel C. Snow and Dennis Orgill

Background: The increased focus on quality and efficiency improvement within academic surgery has met with variable success among plastic surgeons. Traditional surgical performance metrics, such as morbidity and mortality, are insufficient to improve the... View Details

Keywords: Experience and Expertise; Health Care and Treatment; Medical Specialties; Outcome or Result; Performance Efficiency; Performance Improvement

August 2020
Technical Note

Comparing Two Groups: Sampling and t-Testing

By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel

This note describes sampling and t-tests, two fundamental statistical concepts. View Details

Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods

Educators

2011
Article

Scalable Detection of Anomalous Patterns With Connectivity Constraints

By: Skyler Speakman, Edward McFowland III and Daniel B. Neill

We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details

Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic

2013
Book

Keeping Up with the Quants: Your Guide to Understanding and Using Analytics

By: Thomas H. Davenport and Jinho Kim

Managers today need to be able to analyze and make sense of data. They need to be conversant with analytical technology and methods and to make decisions on quantitative analysis. This book offers a variety of practical tools and examples to improve a manager's... View Details

Keywords: Statistics; Business Analytics; Big Data; Analytics and Data Science; Management Practices and Processes; Mathematical Methods; Information Management

2015
Article

Scalable Detection of Anomalous Patterns With Connectivity Constraints

By: Skyler Speakman, Edward McFowland III and Daniel B. Neill

We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details

Keywords: Biosurveillance; Event Detection; Graph Mining; Scan Statistics; Spatial Scan Statistic

Article

Fast Generalized Subset Scan for Anomalous Pattern Detection

By: Edward McFowland III, Skyler Speakman and Daniel B. Neill

We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic... View Details

Keywords: Pattern Detection; Anomaly Detection; Knowledge Discovery; Bayesian Networks; Scan Statistics; Analytics and Data Science

Read Now

Article

Fast Subset Scan for Multivariate Spatial Biosurveillance

By: Daniel B. Neill, Edward McFowland III and Huanian Zheng

We present new subset scan methods for multivariate event detection in massive space-time datasets. We extend the recently proposed 'fast subset scan' framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time... View Details

Keywords: Algorithms; Disease Surveillance; Event Detection; Scan Statistics; Spatial Scan